Methods and systems for adaptive apparel design and apparel information architecture

ABSTRACT

Systems and methods for training a user to label, plan, and code digital files for three-dimensional garment design are provided. Systems and methods regarding a training and recruitment paradigm delivered over mobile to upskill users with manufacturing skills and then staff a newly reshored manufacturing industry over time are also provided.

RELATED APPLICATIONS AND INCORPORATION BY REFERENCE

This application is a continuation of International Application No.PCT/US2020/049682 filed Sep. 8, 2020 and published as InternationalPublication No. WO 2022/055473 on Mar. 17, 2022.

Reference is made to international patent application Serial No.PCT/US20/21740 filed 9 Mar. 2020, which claims priority to U.S.provisional patent application Ser. No. 62/815,280 filed 7 Mar. 2019.

The foregoing applications, and all documents cited therein or duringtheir prosecution (“appln cited documents”) and all documents cited orreferenced in the appln cited documents, and all documents cited orreferenced herein (“herein cited documents”), and all documents cited orreferenced in herein cited documents, together with any manufacturer'sinstructions, descriptions, product specifications, and product sheetsfor any products mentioned herein or in any document incorporated byreference herein, are hereby incorporated herein by reference, and maybe employed in the practice of the invention. More specifically, allreferenced documents are incorporated by reference to the same extent asif each individual document was specifically and individually indicatedto be incorporated by reference.

FIELD OF THE INVENTION

This invention pertains to attracting, training, and contractingcutting, sewing, digital design and machine operators for employment inthe manufacturing industry via a mobile phone, tablet and webbrowser-based software applications.

BACKGROUND OF THE INVENTION

Most unemployed individuals have probably never considered working in agarment factory. Garment factories have a stigma attached to them:dingy, hot, thankless, and an impediment to receiving public benefits.In reality, garment factories of today are clean, well lit, and often inup-and-coming urban areas. Today's garment factories house a mixture oftraditional machines, digital technologies, and new automated equipmentrun by entrepreneurial owners who share millennial and Generation Zvalues of continuous improvement, sustainability, and collaborativedecision-making throughout all levels of the company.

People often learn about new career opportunities from their familymembers', neighbors', and friends' experiences and often do not explorecareer paths outside what is familiar. Beyond this, tackling a newcareer path takes courage and the ability to imagine oneself in a newwork environment, potentially with a new schedule, and performing newunfamiliar tasks. The current pandemic crisis has upended the careertrajectories many held prior to February 2020 and workers need ways toexplore what a new job would be like and build confidence as they learnthe fundamental operations that would underpin the tasks in their newprofession.

Citation or identification of any document in this application is not anadmission that such document is available as prior art to the presentinvention.

SUMMARY OF THE INVENTION

The present invention relates to a digital learning and recruitmentparadigm delivered over mobile phones to upskill workers withmanufacturing skills while they are sheltering in place in the shortterm and then staff a newly reshored manufacturing industry over time.This invention pilots in sewn goods manufacturing with an aim to trainworkers for other manufacturing subsegments later.

The mobile application is downloaded onto iOS and Android devices viaapp stores. Users log into the application using dual authenticationwith their mobile numbers and email addresses.

Once downloaded, the application takes users through a series ofquestionnaires and game-based trainings that test interest, aptitude,and willingness to pursue training (see, e.g., FIGS. 12-18 ).

As users complete active learning games such as sewing machinetrainings, the application capture users' decisions and collects adataset for training future sewing equipment and robotics mental models.

Alongside the software services presented to job seekers, factory hiringmanagers also have the ability to advertise open positions, learn aboutcandidates' skill levels, predict shift attendance, and help workerspredict take-home pay.

Embodiments provided herein include systems and methods for training auser to label and code digital files for three-dimensional garmentdesign. Embodiments provided herein also include system and methods forcollaborative refining of digital and/or physical garment prototypes.

An embodiment includes a system for training a user to label and codedigital files for three-dimensional garment design. The system includes:a database storing at least one digital file including a pattern havingmultiple pattern pieces; a user interface implemented through acomputing device, the user interface configured to provide visual andauditory instructions in a local language of the user for each module ina plurality of learning modules; and computer executable instructionsthat when executed by one or more processors implement the plurality oflearning modules including a setup for cutting module. The setup forcutting module: displays a visual representation of each of the multiplepattern pieces for identification of types of pattern pieces and numbersof pieces to cut; displays identifiers of different types of patternpieces, each identifier including a name of the type of pattern piece inthe local language; displays identifiers for numbers of pattern piecesto cut, each identifier including a name of the number of pattern piecesin the local language; for each pattern piece, receives a selection ofthe visual representation of the pattern piece, receives a selection ofa corresponding identifier for the type of pattern piece, and provides avisual indication of whether the selection of the correspondingidentifier for the type of pattern piece is correct; and for eachpattern piece, receives a selection of a number of pattern pieces to cutand provides a visual indication of whether the selection of the numberof pattern pieces to cut is correct.

In some embodiments, the system also includes computer executableinstructions that when executed by the one or more processors implementa creation of markers for layout module that: provides a visualrepresentation of each of the multiple pattern pieces for layout forcutting with each visual representation including a grain line for thepattern piece; provides a visual representation of material on which tolay out the pattern pieces; displays controls for different types oftransformation operations; receives a selection of at least one of themultiple pattern pieces, a selection of a control for a transformationoperation on the selected at least one pattern piece, and displays avisual representation of the transformation performed on the at leastone pattern piece; and for each of the multiple pattern pieces, receivesa selection of the pattern piece and a movement of the selected patternpiece onto the visual representation of the material and rendering themovement and positioning of the selected pattern piece on a display ofthe user interface.

In some embodiments, the system also includes computer executableinstructions that when executed by the one or more processors implementa digital assembly module that: displays a visual representation of afront side of a three-dimensional model, and a visual representation ofa back side of a three-dimensional model for fitting the pattern to themodel; displays a visual representation of each of the multiple patternpieces for fitting on the three dimensional model; receives a selectionof at least one of the multiple pattern pieces, a selection of a controlfor a transformation operation on the selected at least one patternpiece, and display a visual representation of the transformationperformed on the at least one pattern piece; and for each of themultiple pattern pieces, receives a selection of the pattern piece and amovement of the selected pattern piece onto one of the visualrepresentations of the three-dimensional model and rendering themovement and positioning of the selected pattern piece on the display ofthe user interface.

In some embodiments, the system also includes computer executableinstructions that when executed by the one or more processors implementa pattern piece identification module that: displays examples ofdifferent types of pattern pieces each labeled with the type of patternpiece in the local language; for each example pattern piece, prompts theuser to speak the name of the type of example pattern piece in the locallanguage, and records the spoken name of the type of example patternpiece; and provides data representative of the spoken name of theexample pattern along and an identification of the type of examplepattern piece to a natural language processing system to improve naturallanguage processing of garment-related language in the user's locallanguage with the user's dialect.

In some embodiments, the pattern piece identification module further:displays a visual representation of each of the multiple pattern piecesfor identification of the pattern pieces; displays identifiers ofdifferent types of pattern pieces, each identifier including a name ofthe type of pattern piece in the local language; and for each patternpiece, receives a selection of the visual representation of the patternpiece, receives a selection of a corresponding identifier for the typeof pattern piece, and provides a visual indication of whether theselection of the corresponding identifier for the type of pattern pieceis correct.

In some embodiments, the display of controls for different types oftransformation operations includes display of schematic depictions ofthe transformation operations. In some embodiments, the display ofidentifiers of different types of pattern pieces and the display of theone or more identifiers for numbers of pattern pieces to cut is inresponse to receiving the selection of the visual representation of thepattern piece. In some embodiments, the display of controls fordifferent types of transformation operations is in response to theselection of at least one of the multiple pattern pieces. In someembodiments, the transformation operations include rotate, reflect, andcopy.

In some embodiments, the system further includes computer executableinstructions that when executed by the one or more processors cause theuser interface to: display a login interface to the user; and receiveinformation regarding a username and a password from the user.

In some embodiments, the system further includes computer executableinstructions that when executed by the one or more processors cause thesystem to access information regarding a mobile address of the computingdevice and store the accessed information regarding the mobile addressand information associating the mobile address with a user.

In some embodiments, the system further includes computer executableinstructions that when executed by the one or more processors cause thesystem to store information regarding the users' completion of eachmodule associated with information identifying the user.

In some embodiments, the system further includes computer executableinstructions that when executed by the one or more processors cause thesystem to record information regarding correct and incorrect selectionsby the user, regarding correct and incorrect positioning of patternpieces on the visual representation of the material, regarding correctand incorrect movements of pattern pieces onto the visual representationof the material, and/or regarding correct and in movements of patternpieces onto the visual representations of the three-dimensional model.

In some embodiments, the system further includes computer executableinstructions that when executed by the one or more processors cause thesystem to transmit information to the user via the computing deviceafter completion of one or more modules. In some embodiments, theinformation transmitted is based, at least in part, on one or morescores of the user's performance during one or more of the learningmodules.

In some embodiments, the system further includes computer executableinstructions that when executed by the one or more processors cause theuser interface to display graphical indicators of successful completionof one or more modules within a training session and during one or moreprior training sessions.

In some embodiments, the user interface is implemented and the pluralityof learning modules is implemented as a web-based application on thecomputing device that is hosted by a remote server.

In some embodiments, the computing device includes a touch screen and atleast some of the user selections are received via a touch screeninterface of the computing device.

An embodiment includes method for training a user to label and codedigital files for three-dimensional garment design. The method includes:providing visual and auditory instructions in a local language of theuser on a computing device; displaying a visual representation of eachof the multiple pattern pieces for identification of types of patternpieces and numbers of pieces to cut; displaying identifiers of differenttypes of pattern pieces, each identifier including a name of the type ofpattern piece in the local language; displaying identifiers for numbersof pattern pieces to cut, each identifier including a name of the numberof pattern pieces in the local language; for each pattern piece,receiving a selection of the visual representation of the pattern piece,receiving a selection of a corresponding identifier for the type ofpattern piece, and providing a visual indication of whether theselection of the corresponding identifier for the type of pattern pieceis correct; and for each pattern piece, receiving a selection of anumber of pattern pieces to cut and providing a visual indication ofwhether the selection of the number of pattern pieces to cut is correct.

In some embodiments, the method also includes: providing a visualrepresentation of each of the multiple pattern pieces for layout forcutting with each visual representation including a grain line for thepattern piece; providing a visual representation of material on which tolay out the pattern pieces; displaying controls for different types oftransformation operations; receiving a selection of at least one of themultiple pattern pieces, a selection of a control for a transformationoperation on the selected at least one pattern piece, and displaying avisual representation of the transformation performed on the at leastone pattern piece; and for each of the multiple pattern pieces,receiving a selection of the pattern piece and a movement of theselected pattern piece onto the visual representation of the materialand rendering the movement on a display of the computing device.

In some embodiments, the method also includes: displaying a visualrepresentation of a front of a three-dimensional model and a visualrepresentation of a back of a three-dimensional model for fitting thepattern to the model; displaying a visual representation of each of themultiple pattern pieces for fitting on the three-dimensional model;receiving a selection of at least one of the multiple pattern pieces, aselection of a control for a transformation operation on the selected atleast one pattern piece, and displaying a visual representation of thetransformation performed on the at least one pattern piece; and for eachof the multiple pattern pieces, receiving a selection of the patternpiece and a movement of the selected pattern piece onto the visualrepresentation of the material and rendering the movement on thedisplay.

In some embodiments, the method also includes: displaying examples ofdifferent types of pattern pieces each labeled with the type of patternpiece in the local language; for each example pattern piece, promptingthe user to speak the name of the type of example pattern piece in thelocal language, and recording the spoken name of the type of examplepattern piece; and providing data representative of the spoken name ofthe example pattern along and an identification of the type of examplepattern piece to a natural language processing system to improve naturallanguage processing of garment-related language in the user's locallanguage with the user's dialect.

In some embodiments, the method also includes: displaying a visualrepresentation of each of the multiple pattern pieces for identificationof the pattern pieces; displaying identifiers of different types ofpattern pieces, each identifier including a name of the type of patternpiece in the local language; and for each pattern piece, receiving aselection of the visual representation of the pattern piece, receive aselection of a corresponding identifier for the type of pattern piece,and providing a visual indication of whether the selection of thecorresponding identifier for the type of pattern piece is correct.

In some embodiments, displaying controls for different types oftransformation operations includes displaying schematic depictions ofthe transformation operations. In some embodiments, the displaying ofidentifiers of different types of pattern pieces and the displaying ofthe one or more identifiers for numbers of pattern pieces to cut is inresponse to receiving the selection of the visual representation of thepattern piece. In some embodiments, the displaying of controls fordifferent types of transformation operations is in response to theselection of at least one of the multiple pattern pieces. In someembodiments, the transformation operations include rotate, reflect, andcopy.

In some embodiments, the method also includes: displaying a logininterface to the user; and receiving information regarding a usernameand a password from the user.

In some embodiments, the method also includes: accessing informationregarding a mobile address of the computing device and storing theaccessed information regarding the mobile address and informationassociating the mobile address with a user.

In some embodiments, the method also includes storing informationregarding the users' completion of each module associated withinformation identifying the user.

In some embodiments, the method also includes recording informationregarding correct and incorrect selections by the user, regardingcorrect and incorrect positioning of pattern pieces on the visualrepresentation of the material, regarding correct and incorrectmovements of pattern pieces onto the visual representation of thematerial, and/or regarding correct and in movements of pattern piecesonto the visual representations of the three-dimensional model.

In some embodiments, the method also includes transmitting informationto the user via the computing device after completion of one or moremodules. In some embodiments, the information transmitted is based, atleast in part, on one or more scores of the user's performance duringone or more of the learning modules.

In some embodiments, the method also includes providing graphicalindicators of successful completion of one or more modules within atraining session and during one or more prior training sessions.

In some embodiments, the method is implemented as a web-basedapplication on the computing device that is hosted by a remote server.

In some embodiments, at least some of the user selections are receivedvia a touch screen interface of the computing device.

An embodiment includes a system for collaborative refining of digitaland/or physical garment prototypes. The system includes: a database of aplurality of apparel computer aided design (CAD)-based models; and anapplication accessed via a computing device and communicatively coupledto the database. The application is configured to: receive informationidentifying a first selected apparel CAD-based model of the plurality ofapparel CAD-based models; display a graphical representation of thefirst selected apparel CAD-based model; modify a view of the graphicalrepresentation of the first selected apparel CAD-based model based onuser input received via a user interface of the computing device;display annotation tools for annotation of the first selected apparelCAD-based model and receive input for annotation from a user via theannotation tools or via speech processed via a natural languageprocessing tool; and display an indication of the annotation on thedisplay of the graphical representation of the identified apparelCAD-based model.

In some embodiments, the application is further configured to: store theannotation input associated with the first selected CAD-based modal inthe database and store a time that the input for annotation was receivedor a time that the annotation input was stored; receive from a user, anidentification of a file to be uploaded, associated with the firstselected apparel CAD-based model; and store the identified fileassociated with the first selected apparel CAD-based model in thedatabase.

In some embodiments, the application is further configured to provide anotification to one or more additional users regarding a change in or anaddition to the stored information associated with the first selectedapparel CAD-based model in the database.

In some embodiments the system also includes the application executingon a second computing device. The application executing on the secondcomputing device is configured to: receive information identifying thefirst selected apparel CAD-based model; and display a graphicalrepresentation of the first selected apparel CAD-based model includingan indication of the annotation.

In some embodiments, where the second computing device has a defaultlanguage preference different than a language of the annotation input,the application executing on the second computing device is furtherconfigured to display the annotation input in the default language ofthe second computing device.

In some embodiments, the application executing on the second computingdevice is further configured to: receive a second annotation input froma user of the second computing device; and store the second annotationinput associated with the first selected CAD-based modal in thedatabase.

In some embodiments, the information identifying a first selectedapparel CAD-based model of the plurality of apparel CAD-based modelsobtained from image data acquired from an imaging device of thecomputing device.

In some embodiments, the application is further configured to: displayinformation regarding the identified first selected apparel CAD-basedmodel; and request confirmation of the selection of the identified firstselected apparel CAD-based model.

In some embodiments, the application is further configured to guide auser through a fit session for the identified first selected apparelCAD-based model.

In some embodiments, guiding the user through the fit session for theidentified first selected apparel CAD-based model includes: displaying arequest for one or more photos of a garment corresponding to the firstselected apparel CAD-based model on a fit model and enabling the user toselect one or more photos for upload or displaying one or morepreviously uploaded photos of the garment on a fit model.

In some embodiments, guiding the user through the fit session for theidentified first selected apparel CAD-based model includes: for each ofa plurality of points of measure: providing a graphical description ofthe point of measure; receiving an audio input from a user regarding thepoint of measure; and displaying a numerical value corresponding to theuser's audio input for the point of measure and graphical indicators foracceptance or rejection of the numerical value.

In some embodiments, guiding the user through the fit session for theidentified first selected apparel CAD-based model includes: for each ofthe plurality of points of measure: displaying a graphical indication ofwhether the accepted numerical value corresponding to the user's audioinput for the point of measure is within tolerance for the model.

In some embodiments, guiding the user through the fit session for theidentified first selected apparel CAD-based model includes: displaying aprompt for the user to provide audio comments regarding the fit; andreceiving audio input from the user regarding the fit and displayingcomment text corresponding to the audio input, the audio input convertedto text via natural language processing relying on a garment-specificcorpus of language.

In some embodiments, guiding the user through the fit session for theidentified first selected apparel CAD-based model includes: displayingcomments of other users regarding the apparel CAD-based model or thefit.

In some embodiments, the application is implemented as a web-basedapplication on the computing device that is hosted by a remote server.

Some embodiments include methods implemented by the systems describedherein. Accordingly, it is an object of the invention not to encompasswithin the invention any previously known product, process of making theproduct, or method of using the product such that Applicants reserve theright and hereby disclose a disclaimer of any previously known product,process, or method. It is further noted that the invention does notintend to encompass within the scope of the invention any product,process, or making of the product or method of using the product, whichdoes not meet the written description and enablement requirements of theUSPTO (35 U.S.C. § 112, first paragraph) or the EPO (Article 83 of theEPC), such that Applicants reserve the right and hereby disclose adisclaimer of any previously described product, process of making theproduct, or method of using the product. It may be advantageous in thepractice of the invention to be in compliance with Art. 53(c) EPC andRule 28(b) and (c) EPC. All rights to explicitly disclaim anyembodiments that are the subject of any granted patent(s) of applicantin the lineage of this application or in any other lineage or in anyprior filed application of any third party is explicitly reserved.Nothing herein is to be construed as a promise.

It is noted that in this disclosure and particularly in the claimsand/or paragraphs, terms such as “comprises”, “comprised”, “comprising”and the like can have the meaning attributed to it in U.S. Patent Law;e.g., they can mean “includes”, “included”, “including”, and the like;and that terms such as “consisting essentially of” and “consistsessentially of” have the meaning ascribed to them in U.S. Patent Law,e.g., they allow for elements not explicitly recited, but excludeelements that are found in the prior art or that affect a basic or novelcharacteristic of the invention.

These and other embodiments are disclosed or are obvious from andencompassed by, the following Detailed Description.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

The following detailed description, given by way of example, but notintended to limit the invention solely to the specific embodimentsdescribed, may best be understood in conjunction with the accompanyingdrawings.

FIG. 1 illustrates an exemplary network for adaptive apparel design andapparel information architecture, in accordance with an exemplaryembodiment.

FIG. 2 illustrates user input data entered into the database via anapplication, in accordance with an exemplary embodiment.

FIG. 3 illustrates a high level overview of the adaptive apparel designand apparel information system, in accordance with an exemplaryembodiment.

FIG. 4 illustrates the interaction of the apparel informationarchitecture with different aspects and steps in the apparel designprocess, in accordance with an exemplary embodiment.

FIG. 5 illustrates components that may be included in a data managementplatform of the described methods and systems, in accordance with anexemplary embodiment.

FIGS. 6A-6H are screenshots of a gamified training application thatteaches digital patternmaking and 3D modeling to garment workers, inaccordance with an exemplary embodiment. FIG. 6A is a screenshot of amodule for identification of pattern piece type and an interface forrecording speech corresponding to the identified pattern piece type inthe gamified training application, in accordance with some embodiments.FIG. 6B is a screenshot of a setup for cutting module for identificationof pattern piece type and selection of a number of pieces to cut in thegamified training application in accordance with some embodiments. FIG.6C is screenshot of a creation of markers for layout module for markingthe pattern pieces for layout in the gamified training application inaccordance with some embodiments. FIG. 6D is screenshot of the creationof markers for layout module illustrating a rotation transformation andmovement of a pattern piece, in accordance with some embodiments. FIG.6E is screenshot of a digital assembly module for assembling materialpieces corresponding to the pattern pieces for a first garment on athree dimensional digital model or avatar, in accordance with someembodiments. FIG. 6F is screenshot of a digital assembly module forassembling material pieces corresponding to the pattern pieces on athree dimensional digital model or avatar for a second garment, inaccordance with some embodiments. FIG. 6G is screenshot for a lessonregarding correct and incorrect tension in sewing in a gamified trainingapplication in accordance with an embodiment. FIG. 6H is screenshot fora lesson regarding button placemen in a gamified training application inaccordance with an embodiment.

FIG. 7A is a screen shot illustrating a 3-dimensional (3D) digital modelof a garment displayed on an application for collaborating and refiningof digital and/or physical garment prototypes illustrating display ofthe digital model information and/or links to related digital assets,such as the two dimensional pattern pieces, cost information, technicaldrawings, material properties, in accordance with some embodiments.

FIG. 7B is a screen shot illustrating the 3-dimensional (3D) digitalmodel of the garment displayed on the application illustrating alocalized comment associated with the digital model in accordance withsome embodiments.

FIGS. 8A-8L illustrates interfaces for identifying and designing agarment using a collaboration application, in accordance with anexemplary embodiment. FIG. 8A illustrates a screen shot of thecollaboration application displaying options for entering informationfor identification of a new sample in accordance with an exemplaryembodiment. FIG. 8B illustrates obtaining information for identificationof a new sample via an imaging device of a computing device (e.g., amobile phone) in accordance with an exemplary embodiment. FIG. 8Cillustrates a screen shot requesting confirmation of the identificationof the new sample in accordance with an exemplary embodiment. FIG. 8Dillustrates a screen shot of a display including options for enteringadditional information regarding the identified new sample in accordancewith an exemplary embodiment. FIG. 8E illustrates a screen shot of auser interface for uploading photos of the identified sample inaccordance with an exemplary embodiment. FIG. 8F illustrates a screenshot of a user interface for scheduling a fit date for the sample inaccordance with an exemplary embodiment. FIG. 8G illustrates a screenshot of a user interface displaying information regarding the identifiedsample, the scheduled fit date and other relevant design deadlinesassociated with the sample in accordance with some embodiments. FIG. 8Hillustrates a screen shot of a user interface enabling the user toselect custom points of measurement (POM), which may be saved in theapplication for the user, or standard points of measurement, which maybe standard for the type of garment, for the fit in accordance with someembodiments. FIG. 8I illustrates a screen shot of a user interfaceprompting the user to dictate a value for the displayed POM inaccordance with some embodiments. FIG. 8J illustrates a screen shot of auser interface displaying a value corresponding to the dictated valuefor the point of measurement and requesting confirmation that thedisplayed value corresponds to the dictated value in accordance withsome embodiments. FIG. 8K illustrates a screen shot of a user interfacedisplaying a schematic graphical depiction of the point of measurement,the confirmed value of the measurement, and whether the confirmed valueis within tolerance, and requesting confirmation that the confirmedvalue is correct for the point of measurement in accordance with someembodiments. FIG. 8L illustrates a screen shot of a user interfacedisplaying entered values for the points of measurement and displaying acontrol button to submit the entered values for the points ofmeasurement to be recorded in a database in accordance with someembodiments.

FIGS. 9A-9H illustrate an interface for obtaining and incorporatingfeedback provided by a collaborative application, in accordance with anexemplary embodiment. FIG. 9A illustrates a screen shot of a userinterface of the application for selection of a garment in accordancewith some embodiments. FIG. 9B illustrates a screen shot of a userinterface of the application for selection of a type of information tobe provided or displayed for the selected garment in accordance withsome embodiments. FIG. 9C illustrates a screen shot of a user interfaceof the application for uploading and characterization of photos of thegarment in accordance with some embodiments. FIG. 9D illustrates ascreen shot of a user interface of the application for viewing photos ofthe garment by type of view in accordance with some embodiments. FIG. 9Eillustrates a screen shot of a user interface of the application forproviding comments and viewing comments of others in accordance withsome embodiments. FIG. 9F illustrates a screen shot of an individualcomment received via speech in accordance with some embodiments. FIG. 9Gillustrates a screen shot of a summary or checklist of comments forreview in accordance with some embodiments. FIG. 9H illustrates a screenshot of a list of garments for selection and tracking of garments thathave already been reviewed and addressed in accordance with someembodiments.

FIG. 10 schematically depicts a method for training a user to label andcode digital files for three-dimensional garment design, in accordancewith an exemplary embodiment.

FIG. 11 is a block diagram of an example of a computing device that canbe used to perform one or more steps provided by embodiments describedherein.

FIG. 12 illustrates the workflow of another embodiment.

FIG. 13 provide a method for vetting candidates.

FIG. 14A provides a method for training hand eye coordination, stitchbalancing, stitch quality, signs of needle damage.

FIG. 14B provides a method for training hand eye coordination, stitchbalancing, stitch quality, signs of needle damage related to game pointaccrual.

FIG. 14C provides a method for training identification of sewing needledamage and repair related to game point accrual.

FIG. 14D provides a method for training identification of sewing needledamage and repair related to game point accrual.

FIG. 14E provides a close-up on control panel interface to changefactors and improve sewing output.

FIG. 15 provides a method for teaching remote players sewing stitchidentification.

FIG. 16A provides a method for quantifying skill accrual and schedulingin-person machine-based training.

FIG. 16B provides a method for quantifying skill accrual, planningin-person machine based training and job interviews.

FIG. 16C provides a method for planning work events, notifying workersof open positions, and incentives for training.

FIG. 16D shows the feature set of FIG. 16C as a scrolling, mobileinterface.

FIG. 17A provides a method for quantifying expected payment informationand local tax deduction calculations.

FIG. 17B provides a method for reminding trainee of shift brokeredthrough the app and recording intent to come to work.

FIG. 17C provides an example of method for reminding trainee of shiftbrokered through the app and recording intent to come to work innon-English language.

FIG. 18 provides a method for quantifying worker skills and experiencefor potential employers.

FIG. 19A provides a method for factory hiring manager to post, manage,and recruit for open jobs.

FIG. 19B provides a method for factory production worker planning andjob posting management.

FIG. 20 provides an ecosystem map and the relationship between theembodiment set forth in FIGS. 12-19 and the other applications withinthe Shimmy product portfolio.

DETAILED DESCRIPTION OF THE INVENTION

Disclosed herein are methods and systems that can facilitate efficientand effective communication of design intent through into apparel designand manufacturing.

Apparel brand design teams, patternmakers, and production coordinatorscan benefit from automation in the form of 3-dimensional (3D) designalgorithms. Incorporating these algorithms as part of the workflowlessens the costly product development cycles with physical samplingfrom factories. This assists in assessing the initial fit of a garment,experiment with trim placement, and visualizing what a material or printwould look like.

A major barrier to 3D technology adoption in design departments islimited bandwidth for prep work that needs to be performed. Tasks, suchas labeling digital pattern files and entering data that describesmaterials, trims, and stitches, are difficult. This set-up prep work orpre-work is necessary for implementation of many of these newtechnologies, but the pre-work is often an overwhelming addition to analready full plate.

The skills needed to do this set-up work include knowledge of garmentconstruction, strengths, and limitations of certain sewing machines,different stitches, tension settings, and identification of patternpieces. Sewing machine operators have this knowledge, but many do nothave the technological skills and language skills to provide digitalset-up services to apparel brands.

A digital platform designed especially for sewing machine operators, inaccordance with some embodiments described herein, can overcome literacyand language barriers and enable workers to reskill in the face ofgrowing automation in garment construction and to, in turn, enablemanufacturers in emerging economies to unlock new service businesseswhen manufacturing jobs leave due to automation.

The described methods and systems enable and facilitate a transition toautomated agile apparel manufacturing. The described methods and systemsassist workers in gaining digital skills that allow them to transitioninto higher-skilled work in the factories or to move into other sectors.In some embodiments, the described methods and systems incorporateinnovative cloud applications that drive efficiency and clearcommunication of design intent. In further embodiments, the describedmethods and systems incorporate a platform utilizing artificialintelligence (AI) to build on knowledge and performance over time. Thedescribed methods and systems utilize data that can be used to generate3D blocks faster, speed up product development cycles, and bring moreengineering and feasibility analysis into the design process.Furthermore, some embodiments can be used to train workers to set updatasets and processes that will yield multi-purpose digital models,which may drive brand continuity and feeling as well as speedyproduction across the chain.

Two pilot tests of the described training application (referenced as“Upskill”) were conducted in Dhaka, Bangladesh, to determine whethergarment workers in Bangladesh could effectively use Shimmy Upskill andto identify how the software could be tailored to them. These tests wereconducted with the support of three local factories. The workers whoparticipated in those pilots are referred to herein as a first group anda second group. The first group included 5 female employees, including 3sewing operators, 1 overlock machine operator, and 1 quality assurancechecker. The second group included 6 female employees including 4 sewingoperators and 2 quality assurance checkers. Each pilot followed the samestructure. Most of the participants (10 out of 11) did not ownsmartphones with touchscreen capability. Most of the participants (10out of 11) had never used a computer. Despite their inexperience withthese devices, all testers completed the four training modules withinthe allotted four-hour timeframe. All of the participants werecomfortable with the first two modules, which tested them on patternidentification and cutting. On the other hand, many participants foundthe last module on digital assembly difficult to complete. The result ofthe pilot revealed that symbols, visualizations, and touch screens arekey to addressing users' limited digital literacy. Upskill achieved itsgoal of creating a gamified learning tool. In addition to teachingdigital skills, the software also helped users learn other languages andthe apparel production process.

FIG. 1 illustrates an exemplary network for adaptive apparel design andapparel information architecture 100, in accordance with an exemplaryembodiment. The system 100 includes at least one database 101, anapplication 105, and an adaptive apparel design computing device 110with a processor 113 executing at least a machine learning engine 111, anatural language processing engine 112, and learning modules 114. Thelearning modules may include a setup for cutting module, a creation ofmarkers for layout module, a digital assembly module, and a patternpiece identification module. In some embodiments, the adaptive appareldesign computing device 110 may further include automation technologyapplications. The processor 113 may act as a server, for example, a webserver or an application server. Although the database 101 is shown asremote from the computing device 110, in alternative embodiments, the atleast one database 101 can exist within the computing device 110.Although the machine learning engine 111 is shown as included in theadaptive apparel design device 110, in some embodiments, at least someof or all of the machine learning engine 111 may be implemented in aseparate device or system in communication with the adaptive appareldesign device. Although the natural language processing engine 112 isshown as included in the adaptive apparel design device 110, in someembodiments, at least some of or all of the natural language processingengine 112 may be implemented in a separate device or system incommunication with the adaptive apparel design device 110.

In some embodiments, the application 105 or “app” executes on acomputing device 104 for users such as apparel technical designers. Theapplication 105 may be a desktop application, a mobile application,and/or a web-based application. The computing device 104 may be, forexample, a smartphone, a tablet, a desktop or laptop computer, or someother type of electronic device equipped with a display 106, a camera107, and audio equipment 108. It will be appreciated that the engines111 and 112 may be provided as a series of executable software and/orfirmware instructions.

In some embodiments, the application 105 employs voice-to-textfunctionality, for example, to facilitate recording sample measurementsand fit notes. For example, as described below, a user of theapplication 105 may use voice commands, e.g., speaking a name of garmentpieces in both English and a local language. The data from theapplication 105 is transmitted to the adaptive apparel design computingdevice 110. In some embodiments, the application 105 is built in Angularand hosted on IBM's Bluemix and/or Microsoft Azure.

The adaptive apparel design computing device 110 turns unstructuredpatterns into coded digital elements that can be easily recalled,configured, and run through machine learning engine 111.

As the user inputs data into the application 105, the application 105transmits the data to the adaptive apparel design computing device 110that may analyze and/or save the data, as described herein. For example,the adaptive apparel design computing device 110 may save voicerecordings and responses in the database 101. In some embodiments, thedatabase 101 may be a Firebase database. The adaptive apparel designcomputing device 110 may further collect correlative data from theapplication 105 with the aim to enable future versions of the softwareto help fashion brands and manufacturers speed up design and productionand improve product quality.

In some embodiments, the adaptive apparel design computing device 110 isconfigured to enable a user to efficiently label, code, and generatedigital files ready for 3D design (e.g., digital stitching, etc.). Insome embodiments, the application 105 and the adaptive apparel designcomputing device 110 are designed to accommodate users that are notEnglish speakers, who have limited English-language skills, or that havevarying literacy levels, by displaying vocabulary in English and a locallanguage as well as using symbols when possible. For example, theapplication 105 uses translation to help with learning English andconducting learning activities, such as translating custom sewinginstructions for workers with other languages than that used in thein-country factory.

In an exemplary embodiment, the application 105 is configured to traingarment production workers on digital pattern making, rudimentary 3Dmodeling, and alternative transferable skills, as further describedbelow. The adaptive apparel design computing device 110 may utilizenatural language processing (via natural language processing engine 112)in order to expand into multiple countries/territories where garmentmanufacturers are located (e.g., Bangladesh, Cambodia, Vietnam,Indonesia, Sri Lanka, etc.).

The adaptive apparel design computing device 110 communicates, via acommunications network 112, with the application 105. The communicationsnetwork 112 can be any network over which information can be transmittedbetween devices communicatively coupled to the network. For example, thecommunication network 112 can be the Internet, an Intranet, virtualprivate network (VPN), wide area network (WAN), local area network(LAN), and the like.

In some embodiments, the adaptive apparel design computing device 110and/or the application 105 incorporate automation technologyapplications. In some embodiments, these applications are cloud-based.In some embodiments, the applications are cloud-based with some localdata collection in case of unstable or unreliable internet connection.In some embodiments, the applications at least partially cloud based.Non-limiting examples of such automation technology applications aremobile and web-based based applications for scanning, photography, voicetranscription, and Bluetooth-enabled measurement to automate the processof processing, fitting, and analyzing physical garments in professionaland commercial situations, speech-to-text capturing, and photo and depthsensing data capturing.

The adaptive apparel design computing device 110 and/or the application105 may further incorporate shape recognition software to link patternsand shapes detected in physical garments. For example, if the garmenthas wearable technology affixed to, sewn, or woven in, the shaperecognition software reads data from garment sensor, RFID, and otherdata collection tools to inform new design iterations.

FIG. 2 illustrates user input data entered into the database (e.g.,database 101), in accordance with an exemplary embodiment. For example,a user enters input via user interface(s) displayed on an application(e.g., application 105). The input may include, for example, voicerecordings, user responses, and user authentication. The applicationsaves the input in the database (e.g., database 101), either directly orthrough a computing device (e.g., adaptive apparel design computingdevice 110).

FIG. 3 illustrates a high level overview of the adaptive apparel designand apparel information system, in accordance with an exemplaryembodiment. The application 302 further described in FIGS. 6A-6F (alsoreferenced as “Shimmy Upskill”) provides a digital learning game tousers. The application 304 further described in FIGS. 7A-7D (alsoreferenced as “Shimmy Share”) provides a platform to share 3D models andobtain user comments regardless of a particular computer aided designplatform. Both applications 302 and 304 communicate with a centralcomputing platform 306 (also referenced as “Shimmy Platform” and/or theadaptive apparel design computing device 110). The platform 306, forexample, provides artificial intelligence to identify 2-D shapes andcommon fixes to patterns and sewing based on fit problems, apparelvocabulary, operation instructions in multiple languages, trainingmodules for specific machines and CAD platforms, and certification andapprenticeship credentialing.

FIG. 4 illustrates the interaction of the apparel informationarchitecture 400 with different aspects and steps in the apparel designprocess, in accordance with an exemplary embodiment. In someembodiments, the architecture 400 may be a data management platform. Thearchitecture 400 further illustrates platform layers and how theplatform layers interact with SKU container(s). In some embodiments, thearchitecture 400 may be a cloud-based data architecture. Thearchitecture 400 reflects data taxonomy and descriptors that enable theapparel industry to achieve greater digitalization, automation of designprocesses, and automated garment manufacturing.

In some embodiments, within the described data management platform arecontainers, known as an Apparel SKU Container 401, for data pertainingto a particular stock keeping unit (SKU) of apparel. Each containerholds information such as, but not limited to one or more of: athree-dimensional (3D) model, Bill of Materials, sewing instructions,two-dimensional (2D) pattern files, a tech pack, prototype history,sketches, photographs, texted and spoken comments, and other digitalartifacts that aided in the design, planning, engineering, development,marketing, manufacture, transportation, sale, use, and end-of-lifereclamation of the garment.

In some embodiments, each container serves as a single point of truthfor the large teams who design, develop, market, sell, and reclaimgarments. These various functions need to interact with this data atdifferent levels of complexity and for different outcomes (for example,a 3D visualization needed for augmented reality versus a technicalsizing grade rule needed for batch manufacturing). In some embodiments,the container can expose slices of data in ways that benefit differentusers while keeping track of versions, additions, and changes whiletracing ancestry back to the Apparel SKU in the event of any downstreamapplications of the data within the platform or outside of it via adigital watermark within the code.

In some embodiments, the container is situated on the platform amongstother containers related to it (e.g., the SKUs were sold at the sametime as part of a line, they originated from design elements within aparticular apparel block, and they belong to a similar product classlike “skirts”).

The platform layers include upper transactional layers 404, a familiallayer 408, a foundational layer 410, and a lower foundational layer 406.

The upper transactional layers 404 are externally facing layers wherethird parties can interact with the information within the apparel SKUcontainer. The owner or controller of the apparel SKU container canlimit which data is exposed and through which user interfaces andapplications that the third party uses the data. The upper transactionallayer 404 enables third parties to utilize product data, at the owner'sdiscretion, to visualize it, market it, or build from it in a newdesign.

The lower transaction layer 406 allows third parties to supply data,digital services (e.g., 3D modeling, material science, digitalsimulations), and applications that are interoperable with thisplatform.

The familial layer 408 holds the SKU containers themselves and allowsfor recall, correlation between them, and data visualization.

The foundational layer 410 includes architecture that enables outsideand inside datasets to pass into the platform and for that informationto be represented within a particular apparel SKU container. Thearchitecture forms the basis for multi-parameter decision-making andcomputational problem solving within 2D, 3D, and manufacturing andmerchandizing planning software.

Some embodiments incorporate automation technology applications. In someembodiments, these applications are at least partially cloud based. Insome embodiments, these applications interact with apparel SKUcontainers. Non-limiting examples of such automation technologyapplications are mobile and web-based based applications using scanning,photography, voice transcription, and Bluetooth-enabled measurement toat least partially automate the process of processing, fitting, andanalyzing physical garments in professional and commercial situations(e.g., a front-end apparel sample measurement application). Non-limitingexamples of tasks accomplished through automation technologyapplications and the platform technology are speech-to-text capturing,and photo and depth sensing data capturing.

Some embodiments further incorporate cloud-based application(s) thatutilizes shape recognition software to link patterns and shapes detectedin physical garments with Apparel SKU containers on the platform oraccessed via the 3rd party exchange within the transactional layer404/406. The cloud-based application analyzes user wear patterns throughto grade rules within the Apparel SKU container. If the garment haswearable technology affixed to, sewn, or woven in, the application willread data from garment sensor, RFID, and other data collection tools toinform new design iterations. The cloud-based application routesend-customer return and fit impressions back from retailers, e-commerceshipping processors, and online comments through to the Apparel SKUContainer and its related blocks and styles for grading adjustments.

The cloud-based application may further include a computational designengine that solves for optimal construction based on multiple parameterslike cost, manufacturability, sustainability, and fit.

FIG. 5 illustrates components that may be included in a data managementplatform 500 of the described methods and systems, in accordance with anexemplary embodiment.

The data management platform 500 includes a front-end appareldevelopment application 502. The application 502 may be used, forexample, for speech to text capturing, and photo and depth sensing datacapturing during apparel development.

The data management platform 500 includes a front-end apparel samplemeasurement application 504. The application 504 may be used, forexample, for speech to text capturing, and photo and depth sensing datacapturing during apparel sample measurement.

Non-limiting examples of such applications 502 and 504 are mobile andweb-based based application using scanning, photography, voicetranscription, and Bluetooth-enabled measurement to automate the processof processing, fitting, and analyzing physical garments in professionaland commercial situations.

The data management platform 500 includes a design configurator andoptimization engine 506. The design configurator and optimization engine506 performs shape recognition, correspondence identification, andconfiguration of pattern pieces.

The data management platform 500 includes generating and optimizing 2Dpattern shapes for manufacturing 508.

The data management platform 500 includes a back-end data entryweb-based application 510.

The data management platform 500 includes an application programminginterface (API) connection(s) 510 to CAD, product lifecycle management,and ERP systems (e.g., an interface for the adaptive apparel designcomputing device 110 and/or the application 105 to communicate with CAD,product lifecycle management, and Enterprise resource planning (ERP)systems. The data management platform 500 includes controllers 514. Thecontrollers 514 may include machine tool controllers. For example, thecontrollers 514 may control automated fabric spreading, sewing, andcutting machines (e.g., Sewbots® and other automated sewing robots).

One of ordinary skill in the art will appreciate that some embodimentsmay not include all components and some embodiments may not include allof the described features. Further, in some embodiments, thefunctionality of multiple components may be incorporated into a singlecomponent or fewer components.

FIGS. 6A-6F are screenshots of a gamified training application (e.g.,application 105) that teaches digital patternmaking and 3D modeling togarment workers, in accordance with an exemplary embodiment. Theapplication utilizes a design user interface similar to apparel industryCAD systems to upskill and reskill garment workers in factories. Theapplication addresses a significant challenge facing the apparelindustry involving a lack of digital workers to make digital models. Theapplication trains a user in apparel vocabulary and operationinstructions in English and in a native language of the user, which maybe referred to herein as a local language. The application furthercreates garment/apparel taxonomy using specific set of definitions andbuilds a corpus to be used in the application.

The application is a game that is also a learning and work tool. Theapplication assists users develop cognitive and technical skills withdigital patternmaking, 3D digital sewing assemblies, automated equipmentoperation and maintenance, and other digital literacy skills. Some ofthe advantages of some embodiments of this application include one onone feedback delivered immediately with adaptive rewards andconstructive feedback. In addition, goals (e.g., in the form of trainingmilestones and/or work milestones) in a game environment are defined andeasier to understand than interpreting the meaning inside a teacher ormanager's verbal directive. Upskill also provides the user with theopportunity to work in groups and create collective intelligence acrossgeographies and cultural divides.

The application may use artificial intelligence (AI) to train garmentworkers on basic digital patternmaking, 3D digital sewing assemblies,and other digital literacy skills like English and interface use. Insome embodiments, the main features of the application include voicenarration in a local language of the user (e.g., Bangla), display ofvideo instructions in the local language, voice-to-text functionality inrecalling pattern pieces, symbols, and visualization to guide users, abackend database to save responses from users, and touch-screenfunctionality. In some embodiments, the application trains or providesinput to train an artificial intelligence platform (e.g., Microsoft'sartificial intelligence platform, Microsoft Cognitive Services), torecognize an apparel vocabulary in a foreign language, such as Banglaapparel vocabulary, and align it with shapes and English words.

In some embodiments, the application is designed around Bloom'sTaxonomy, a learning framework that ensures learners apply what has beenlearned. The model consists of six educational objectives: remember,understand, apply, analyze, evaluate, and create. The application guidesusers through the levels of Bloom's Taxonomy with active learning andmultimedia modules focused on 3D, cut planning, multi-skilled sewing,dexterity, machine maintenance, and digital patternmaking.

The application includes voice narration in the user's local language(e.g., Bangla) to help explain module instructions. In some embodiments,the application also includes video instructions to guide users on howto work through different learning modules. In some embodiments, thevoice to text functionality mentioned above is integrated into theapplication to aid in recalling pattern pieces.

In some embodiments, the application may be a web-based application, anda user (e.g., a garment worker) may be provided with login informationso that the user can access the web-based application. The user (e.g.,garment worker) logs into the application and is guided through a seriesof learning modules, as shown in FIG. 6A-6F. In some embodiments, theapplication is provided to the user via a computing device that enablestouch screen input. In some embodiments, the user selects a module via adisplay on the touch screen and follows the instructions displayed inwords and symbols. The user (e.g., garment worker) can also select adisplayed option to play a recorded voice with instructions. In someembodiments, a trainer/administrator may also log into a backend of theapplication to create accounts, reset passwords, and look at the resultsdata being collected by the users (e.g., garment workers) using theinterface.

In one embodiment, the application includes the following modules:apparel pattern identification, setup for cutting, creation of markers,and digital assembly.

In some embodiments, the application may be a cloud-based applicationthat utilizes shape recognition software to link patterns and shapesdetected in physical garments with Apparel SKU containers on theplatform or accessed via the 3rd party exchange within the transactionallayer.

FIG. 6A illustrates an interface of the application for apparel patternidentification. The user is shown a visual representation of a garment602 (i.e., a dress shirt, dress, pants, etc.) and visual representationsof types of pattern pieces 604 (e.g., shapes of pattern pieces needed tocreate the garment) that are included in a pattern for the garment 602(i.e., front, back, collar band, sleeve, collar, cuff, yoke, etc.). Eachtype of pattern piece has an associated name that is shown in the locallanguage, or in the local language and English. A record button 606 isassociated with each type of pattern piece such that the user can recordthe pronunciation of the type of pattern piece in the local language, orin the local language and English. The pronunciation is stored in adatabase. In some embodiments, there is a visual indication when therecording has been saved (e.g., the record button 606 turns blue and/orshows (“Done”) when the voice recording has been saved.) The user canuse the record button 606 to record apparel vocabulary words spoken bythe user. Once identification of all pieces for a pattern for a garmentis completed, the user can select a button to move on to another garmentto perform apparel pattern piece identification for that garment.

FIG. 6B illustrates an interface of the application for setup forcutting. The user is tasked with identifying the pattern pieces by nameas performed in FIG. 6A. The user can also add the number of times thepattern piece is used to make a complete garment. The user can do thisby voice or by touching the screen.

The user selects or clicks on a pattern piece 608 for a garment 609,which populates a sidebar or column 610 with potential names 612 of thepattern piece 608 and a potential number of times 614 the pattern piece608 is used to make the garment 609. The user must user choose thecorrect name, which is also referred to as type, of the pattern piece608 from the potential names (potential types) in the sidebar 610 andthe number of times 614 the pattern piece 608 is used to make thegarment 609 (for example, it may require cutting two sleeve patternpieces to make the garment). The names may be presented in Englishand/or the local language (e.g., Bahasa and/or Bahasa Indonesian).

The user performs the above actions for all the presented pattern piecesand identifies the type of pieces from the column 610. In someembodiments, the user is assessed based on the number of correctanswers. Once done, the user can select a button to move on to anothergarment to perform a setup for cutting for that garment.

In some embodiments, information regarding the performance of a user orof multiple users of the application may be provided to a supervisor,administrator, or employer via an analytics interface to get baselineskills assessment and training data/results. Employers may achieve asustainable workforce by training factory workers, who will thentransition to higher skilled, higher paying jobs and grow more dedicatedto their company.

FIG. 6C illustrates an interface of the application for creation ofmarkers. A plan for cutting the garment in the fabric is called a markeror a layout. Before any cutting begins, the marker is used to determinehow much fabric is being used per garment. This calculation is calledconsumption and is tied to the cost of the garment. In the interface,the user creates a marker for cutting the pattern pieces out of thefabric. The user places pattern pieces on the cloth (represented by agrey rectangle 616) in a way that minimizes waste. The user selects thepattern pieces 618 to relocate on the grey rectangle 616) in a way thatminimizes waste. The user can rotate, flip, and copy each pattern piece618 by clicking the buttons 620 on the top right hand corner.

FIG. 6D illustrates another interface of the application for creation ofmarkers.

FIG. 6E illustrates an interface of the application for digitalassembly. In the Digital Assembly module, the user lays down patternpieces 622 on a three dimensional model or avatar 624. The useridentifies the pattern pieces and the cut count. Users can also flip,rotate, and copy pieces to lay onto the avatar by clicking the buttons620.

FIG. 6F illustrates another interface of the application for digitalassembly.

FIGS. 6G and 6H illustrate another interface of an application fordigital assembly, in accordance with some embodiments. FIG. 6G is aninterface for a lesson regarding correct and incorrect tension in sewingin accordance with an embodiment. FIG. 6H is an interface for a lessonregarding button placement in accordance with an embodiment.

In some embodiments, the user interface prompts the user to providelogin information (e.g., a user name and password). In some embodiments,the user will log in using a mobile address. In some embodiments, theapplication will continue to engage the user in knowledge retention,incentives for continuing study, and useful technical tips after thetraining session is completed, e.g., by follow up messages in theapplication, via email, via text, or via other messaging applications ormodes. The described systems and methods can be designed so that as auser of the training and work application (e.g., a garment worker) movesthrough exercises and operations, input from the user can be employed tobuild a dataset and train an AI that is useful for automating productdesign and development workflows. There is a technical demand for theinstitutional knowledge sewing machine operators possess. Someembodiments can leverage that knowledge and build upon it though thedesign of back end user interfaces that facilitate future work forcurrent sewing machine operators to use their knowledge in turningunstructured patterns into digital files ready for 3D designs.

FIGS. 7A and 7B illustrate 3-dimensional (3D) digital model 702 of agarment displayed on an application, in accordance with an exemplaryembodiment. For example, the garment may be the one of the garmentsdesigned in FIGS. 6A-6F. Pieces of material needed to create thedisplayed garment are shown within a section 704 associated with thedigital model 702. Additional information about the displayed garment isshown within a section 706 associated with the digital model 702. FIG.7A illustrates the interface where the digital model is being displayedwith links to related digital assets, such as the two-dimensionalpattern pieces, cost information, technical drawings, materialproperties, etc.

3D digital models are used to build digital prototypes of garments sothe design can be evaluated without having to sew a physical prototype.3D digital models can further be utilized to judge the fit of a garmenton a digital body to make sure the pattern was made correctly. Apparelbrands, manufacturers, and retailors in remote locations can also viewand make decisions about the design without having to ship a physicalprototype. 3D digital models can also be used to assist a consumer ofclothing to view the garment as a 360-degree digital model on a websiteor in an AR/VR consumer experience. The described systems and methodscan assist in building the capacity of garment workers to create digitalmodels to enable these use cases over time. 3D design will increasetime-to-market by building a common language that allows brands andmanufacturers to reduce physical prototypes and design errors.

The application (e.g., application 105) is web-based collaborationapplication that assists in the process of refining digital and physicalgarment prototypes. In an exemplary embodiment, the application is aweb-based 3D viewer, accessible from laptop, tablets, or a phone, thatcan consume a digital model 702 built in an apparel CAD program anddisplay it for easy viewing, manipulation, and annotation. Utilizing theviewer, the digital model 702 can be spun 360 degrees, zoomed in or out,annotated, and drawn on using a stylus or fingertip. The users can makelocalized comments directly on the digital model and add pictures,video, and uploads of files like Excel documents, PDFs, or Illustratorfiles. The comments will display as tags on the 3D model 702 as well asin a time-stamped checklist where a user can indicate that the commenthas been addressed. FIG. 7B illustrates a localized comment 708 placedin association with the digital model. The comment 708 includes anuploaded picture 710. The comment 708 will display as a tag on the 3Dmodel 702 as well as in a time-stamped checklist 712 where a user canindicate that the comment has been addressed.

The comments are automatically translated into the user's preferredlanguage by using Natural Language Processing and a corpus with apparelvocabulary and domain expertise. The corpus, in at least some languages,may be built or obtained, at least in part, from input from users of thetraining/learning and work tool application.

The 3D digital model 702 is displayed in the application on a computingdevice (e.g., computing device 104). In some embodiments, the adaptiveapparel design computing device 110 is configured to enable a user toefficiently label, code, and generate digital file(s) ready for 3Ddesign (e.g., digital stitching, etc.). The adaptive apparel designcomputing device 110 transmits the digital file(s) to a web-based 3Dviewer. The web-based 3D viewer displays the 3D design based on thedigital file(s).

In some embodiments, the computing device may further use artificialintelligence during digital product creation and/or during testingsimulation, such as generating predictions on how material is affectedby certain conditions such as stretching, heat, etc., and generatingpredictions regarding fit problems based on size, materials, patterndesign.

FIGS. 8A-8L illustrates interfaces for identifying and designing agarment, in accordance with an exemplary embodiment. In particular, asexplained further below, a user enters information on a first garmentsample and schedules a date and a time to try on the first garmentsample.

FIGS. 8A-8E illustrate interfaces on the application for enteringinformation on a garment, for example, by scanning a garment tag orgarment paperwork. The garment paperwork may include, for example, astyle, a fit, and a vendor. A user may enter additional details on thegarment, such as selecting the garment type, as shown in FIG. 8D.

FIG. 8F illustrates an interface for selecting a fit date to try on thegarment identified in FIGS. 8A-8C.

FIG. 8G illustrates an interface displaying a summary of the informationfrom FIGS. 8A-8F. The information may include a description, garmenttype, sample iteration, vendor/factory, sample received date, estimatedfit date, delivery date, and fit approval date.

FIGS. 8H-8K illustrate interfaces on the application for entering valuesfor points of measurements for the garment identified in FIGS. 8A-8C.The points of measurements may be used to design the garment.

FIG. 8L illustrates an interface displaying a summary of themeasurements from FIGS. 8H-8K.

FIGS. 9A-9H illustrate an interface for obtaining and incorporatingfeedback on the garment of FIGS. 8A-8L, in accordance with an exemplaryembodiment. In particular, as explained further below, a user receivescomments and/or feedback on the first garment sample, and creates asecond garment sample based on the comments and feedback.

FIGS. 9A-9B illustrate an interface on the application enabling a userto selecting a garment for the fitting.

FIGS. 9C-9D illustrate an interface on the application enabling the userto add images of the garment during the fitting to the application.

FIGS. 9E-9G illustrate an interface on the application enabling users toenter comments on the garment. Team members can add comments to the feedremotely. Shimmy data capsule is ready to push to PLM, Excel, materialor job-tracking software, or email. An application records samplemeasurements and fit notes, for example in sample rooms, sessions withfit models, and on the factory floor.

FIG. 9H illustrates an interface on the application for selecting a nextgarment.

FIG. 10 is a method 1000 for training a user to label and code digitalfiles for three-dimensional garment design, in accordance with anexemplary embodiment. At step 1002, the method includes providing visualand auditory instructions in a local language of the user. At step 1004,the method includes displaying a visual representation of each of themultiple pattern pieces for identification of types of pattern piecesand numbers of pieces to cut. At step 1006, the method includesdisplaying identifiers of different types of pattern pieces, eachidentifier including a name of the type of pattern piece in the locallanguage. At step 1008, the method includes displaying identifiers fornumbers of pattern pieces to cut, each identifier including a name ofthe number of pattern pieces in the local language. For each patternpiece, at step 1010, the method includes receiving a selection of thevisual representation of the pattern piece, receiving a selection of acorresponding identifier for the type of pattern piece, and providing avisual indication of whether the selection of the correspondingidentifier for the type of pattern piece is correct. For each patternpiece, at step 1012, the method includes receiving a selection of anumber of pattern pieces to cut and providing a visual indication ofwhether the selection of the number of pattern pieces to cut is correct.At step 1014, the method includes providing a visual representation ofeach of the multiple pattern pieces for layout for cutting with eachvisual representation including a grain line for the pattern piece. Atstep 1016, the method includes providing a visual representation ofmaterial on which to lay out the pattern pieces. At step 1018, themethod includes displaying controls for different types oftransformation operations. At step 1020, the method includes receiving aselection of at least one of the multiple pattern pieces, a selection ofa control for a transformation operation on the selected at least onepattern piece, and displaying a visual representation of thetransformation performed on the at least one pattern piece. For each ofthe multiple pattern pieces, at step 1022, the method includes receivinga selection of the pattern piece and a movement of the selected patternpiece onto the visual representation of the material and rendering themovement on the display. At step 1024, the method includes displaying avisual representation of a front of a three-dimensional model, and avisual representation of a back of a three-dimensional model for fittingthe pattern to the model. At step 1026, the method includes displaying avisual representation of each of the multiple pattern pieces for fittingon the three-dimensional model. At step 1028, the method includesreceiving a selection of at least one of the multiple pattern pieces, aselection of a control for a transformation operation on the selected atleast one pattern piece, and displaying a visual representation of thetransformation performed on the at least one pattern piece. For each ofthe multiple pattern pieces, at step 1030, the method includes receivinga selection of the pattern piece and a movement of the selected patternpiece onto the visual representation of the three-dimensional model andrendering the movement on the display.

FIG. 11 is a block diagram of an example computing device 1100 that canbe used to perform one or more steps provided by embodiments describedherein. In an exemplary embodiment, computing device 1100 is a computingdevice 104 and/or a computing device 110 shown in FIG. 1 . Computingdevice 1100 includes one or more non-transitory computer-readable mediafor storing one or more computer-executable instructions or software forimplementing embodiments described herein. The non-transitorycomputer-readable media can include, but are not limited to, one or moretypes of hardware memory, non-transitory tangible media (for example,one or more magnetic storage disks, one or more optical disks, one ormore USB flash drives), and the like. For example, a memory 1106included in computing device 1100 can store computer-readable andcomputer-executable instructions or software for implementingembodiments described herein. Computing device 1100 can also include aprocessor 1102 and an associated core 1104, and optionally, one or moreadditional processor(s) 1102′ and associated core(s) 1104′ (for example,in the case of computer systems having multiple processors/cores), forexecuting computer-readable and computer-executable instructions orsoftware stored in memory 1106 and other programs for controlling systemhardware. Processor 1102 and processor(s) 1102′ can each be a singlecore processor or multiple core (1104 and 1104′) processor. Computingdevice 1100 may further include an AR item generator engine.

Virtualization can be employed in computing device 1100 so thatinfrastructure and resources in the computing device can be shareddynamically. A virtual machine 1114 can be provided to handle a processrunning on multiple processors so that the process appears to be usingonly one computing resource rather than multiple computing resources.Multiple virtual machines can also be used with one processor.

Memory 1106 can include a computer system memory or random accessmemory, such as DRAM, SRAM, EDO RAM, and the like. Memory 1106 caninclude other types of memory as well, or combinations thereof. In someembodiments, a customer can interact with computing device 1100 througha visual display device, such as a touch screen display or computermonitor, which can display one or more customer interfaces that can beprovided in accordance with embodiments. The visual display device mayalso display other aspects, elements and/or information or dataassociated with embodiments. Computing device 1100 may include other I/Odevices for receiving input from a customer, for example, a keyboard orany suitable multi-point touch interface, such as a pointing device(e.g., a pen, stylus, mouse, or trackpad). The keyboard and pointingdevice may be coupled to visual display device. Computing device 1100may include other suitable conventional I/O peripherals.

For example, where computing device 1100 is a mobile computing device(such as computing device 104), computing device 1100 may include atouch screen display, a camera, and a location module, and may executean application that displays a map of the facility and displays virtualitems in augmented reality.

Computing device 1100 can also include one or more storage devices 1124,such as a hard-drive, CD-ROM, or other computer-readable media, forstoring data and computer-readable instructions and/or software.Exemplary storage device 1124 can also store one or more storage devicesfor storing any suitable information required to implement embodiments.

Computing device 1100 can include a network interface 1112 configured tointerface via one or more network devices 1120 with one or morenetworks, for example, Local Area Network (LAN), Wide Area Network (WAN)or the Internet through a variety of connections including, but notlimited to, standard telephone lines, LAN or WAN links (for example,802.11, T1, T3, 56 kb, X.25), broadband connections (for example, ISDN,Frame Relay, ATM), wireless connections, controller area network (CAN),or some combination of any or all of the above. The network interface1112 can include a built-in network adapter, network interface card,PCMCIA network card, card bus network adapter, wireless network adapter,USB network adapter, modem or any other device suitable for interfacingcomputing device 1100 to any type of network capable of communicationand performing the operations described herein. Moreover, computingdevice 1100 can be any computer system, such as a workstation, desktopcomputer, server, laptop, handheld computer, tablet computer (e.g., theiPad® or Microsoft Surface® tablet computer), mobile computing orcommunication device (e.g., the iPhone® communication device), or otherform of computing or telecommunications device that is capable ofcommunication and that has sufficient processor power and memorycapacity to perform the operations described herein.

Computing device 1100 can run any operating system 1116, such as any ofthe versions of the Microsoft® Windows® operating systems, the differentreleases of the Unix and Linux operating systems, any version of theMacOS® for Macintosh computers, any embedded operating system, anyreal-time operating system, any open source operating system, anyproprietary operating system, any operating systems for mobile computingdevices, or any other operating system capable of running on thecomputing device and performing the operations described herein. Inexemplary embodiments, the operating system 1116 can be run in nativemode or emulated mode. In an exemplary embodiment, the operating system1116 can be run on one or more cloud machine instances.

In an advantageous embodiment, the present invention also relates tomethods and systems that can facilitate efficient and effective hiringof new workers into manufacturing jobs aiding in growing the flexible,skilled workforce needed to reshore manufacturing. The method andsystems described are made possible by a reciprocal apprenticingartificial intelligence engine that delivers adaptive training, but alsocaptures worker inputs and feeds back a user's latent problem-solvinginstincts. These data points aid in the better design of user interfacesfor machine controllers.

Sewn goods manufacturers have a difficult time recruiting new workforceentrants. This mobile application helps potential workers see 360 degreevideo of a sewing or other work station inside a garment manufacturingfacility, hear the sounds of the space, watch testimonials from workers,and feel the vibration of the machine simulated through their phone.

Sewn goods skill trainers often suffer from trainees beginning theirtrainings and not seeing the course through to completion, wastingtrainer resources, and not achieving the end goal of more fully-trainedworkers entering the job market.

Sewn goods skill trainers use outdated, manual methods to train newworkers that rely on workers attending in-person training programs forup to 46 weeks of training to get a trainee to proficiency.

The application provides training, employment, and reminder content inmultiple languages by utilizing artificial intelligence for dynamiclanguage translation.

The application connects to employment sites and feeds in local jobopportunities that match trainees' skill levels.

The application helps trainees understand wages, tax deductions, and thelogistical realities of commuting to the job via partner APIs andpublicly available datasets.

The application allows hired workers to indicate their commitment toattend the shift, aiding in better workforce predictions and betterthroughput estimates to a factory's customers.

The application enables factory hiring managers to predict how manyworkers will attend upcoming shifts.

The application enables factory hiring managers to vet candidates withinthe app and schedule interviews.

The application utilizes game interfaces to test hand-eye coordination,eyesight, and dexterity related to material handling.

The application teaches stitch identification and teaches trainees whatthe most common machines in a factory look like.

The application uses game mechanics to teach what kind of thread is usedfor various types of garments.

The application uses game mechanics to teach the difference betweenwoven and knit fabrics.

The application uses game mechanics to teach which stitches are used forKnits: 504, 406, 401 and which are for Wovens: 301, 516 (401 & 504combined). Users are able to ID the stitches by sight at mastery of thelearning module.

The application uses game mechanics to teach stitch count and threadsize selection for fabrics that impacts sewing output.

The application uses game mechanics to teach stitch quality standardsand identify defects. I.e. what is a good balanced stitch vs. a badimbalanced stitch.

The application uses game mechanics to teach machine adjustments andbasic maintenance.

The application uses game mechanics to teach users what to do when aneedle is damaged, causing stitch formation to be off standard.

FIG. 12 is a method for training a user to measure human skills 1201,provide the previously described training application (referenced as“Upskill”) 1202, provide machine based training 1203 and deliverqualified trainees to in-person sewn trades practioners intraining/vetting/placement financial coaching 1204 in accordance with anexemplary embodiment. Between each of 1201, 1202, 1203 and 1204, a userwill either pass or fail the learning games. A “pass” enables the userto proceed to the next step and a “fail” enables the user to eitherretry or stop the previous step. Regardless of a “pass” or “fail” innateworker aptitude for tasks will be recorded to ensure that workers aredirected towards career paths with work that aligns with their interestsand abilities.

At step 1201, the application takes users through a series ofquestionnaires and game-based trainings that test interest, aptitude,and willingness to pursue training.

Step 1202 provides the core Shimmy Upskill curriculum which is adaptedto include the design and manufacture of personal protective equipment(“PPE”), such as face masks, as a digital learning game to users. Theplatform 1202, for example, provides artificial intelligence to identify2-D shapes and common fixes to patterns and sewing based on fitproblems, apparel vocabulary, operation instructions in multiplelanguages, training modules for specific machines and CAD platforms, andcertification and apprenticeship credentialing. The application utilizesa design user interface similar to apparel industry CAD systems toupskill and reskill garment workers in factories. The applicationaddresses a significant challenge facing the apparel industry involvinga lack of digital workers to make digital models. The application trainsa user in apparel vocabulary and operation instructions in English andin a native language of the user, which may be referred to herein as alocal language. The application further creates garment/apparel taxonomyusing specific set of definitions and builds a corpus to be used in theapplication. The application is a game that is also a learning and worktool. The application assists users develop cognitive and technicalskills with digital patternmaking, 3D digital sewing assemblies,automated equipment operation and maintenance, and other digitalliteracy skills. Some of the advantages of some embodiments of thisapplication include one on one feedback delivered immediately withadaptive rewards and constructive feedback. In addition, goals (e.g., inthe form of training milestones and/or work milestones) in a gameenvironment are defined and easier to understand than interpreting themeaning inside a teacher or manager's verbal directive. Upskill alsoprovides the user with the opportunity to work in groups and createcollective intelligence across geographies and cultural divides.

Step 1203 provides machine basics. As users complete active learninggames such as sewing, the application capture users' decisions andcollects a dataset for training future sewing equipment and roboticsmental models. The application utilizes game interfaces to test hand-eyecoordination, eyesight, and dexterity related to material handling. Theapplication teaches stitch identification and teaches trainees what themost common machines in a factory look like. The application uses gamemechanics to teach what kind of thread is used for various types ofgarments. The application uses game mechanics to teach the differencebetween woven and knit fabrics. The application uses game mechanics toteach which stitches are used for Knits: 504, 406, 401 and which are forWovens: 301, 516 (401 & 504 combined). Users are able to identify thestitches by sight at mastery of the learning module. The applicationuses game mechanics to teach stitch count and thread size selection forfabrics that impacts sewing output. The application uses game mechanicsto teach stitch quality standards and identify defects, such as what isa good balanced stitch vs. a bad imbalanced stitch. The application usesgame mechanics to teach machine adjustments and basic maintenance. Theapplication uses game mechanics to teach users what to do when a needleis damaged, causing stitch formation to be off standard.

Step 1204 provides sewn trades workforce participantstraining/vetting/placement financial coaching. The application connectsto employment sites, in-person training, and feeds in local jobopportunities that match trainees' skill levels. The application helpstrainees understand wages, tax deductions, and the logistical realitiesof commuting to the job. The application allows hired workers toindicate their commitment to attend the shift, aiding in betterworkforce predictions and better throughput estimates to a factory'scustomers. The application enables factory hiring managers to predicthow many workers will attend upcoming shifts. The application enablesfactory hiring managers to vet candidates within the app and scheduleinterviews.

FIG. 13 provide a method for vetting candidates. FIG. 13 illustrates ascreen shot of a user interface for asking users if they are interestedin working in a factor, if they learned how to sew and to provide timesin which a user is available to work.

FIG. 14A provides a method for training hand eye coordination, stitchbalancing, stitch quality, signs of needle damage.

FIG. 14B illustrates a screen shot for a method for training hand eyecoordination, stitch balancing, stitch quality, signs of needle damagerelated to game point accrual.

FIG. 14C provides a method for training identification of sewing needledamage and repair related to game point accrual.

FIG. 14D provides a method for training identification of sewing needledamage and repair related to game point accrual.

FIG. 14E provides a close-up on control panel interface to changefactors and improve sewing output.

FIG. 15 provides a screen shot for a method for teaching remote playerssewing stitch identification.

FIG. 16A provides a screen shot for provides a method for quantifyingskill accrual and scheduling in-person machine-based training.

FIG. 16B provides a screen shot for provides a method for quantifyingskill accrual, planning in-person machine based training and jobinterviews.

FIG. 16C provides a screen shot for a method for planning work events,notifying workers of open positions, and incentives for training.

FIG. 16D provides a screen shot for shows the feature set of FIG. 16C asa scrolling, mobile interface.

FIG. 17A provides a screen shot for a method for quantifying expectedpayment information and local tax deduction calculations.

FIG. 17B provides a screen shot for a method for reminding trainee ofshift brokered through the app and recording intent to come to work.

FIG. 17C provides a screen shot for an example of method for remindingtrainee of shift brokered through the app and recording intent to cometo work in non-English language.

FIG. 18 provides a screen shot for a method for quantifying workerskills and experience for potential employers.

FIG. 19A provides a screen shot for a method for factory hiring managerto post, manage, and recruit for open jobs.

FIG. 19B provides a screen shot for a method for factory productionworker planning and job posting management.

FIG. 20 provides an ecosystem map and the relationship between theembodiment set forth in FIGS. 12-19 and the other applications withinthe Shimmy product portfolio.

In particular, FIG. 20 illustrates a high level overview of the adaptiveapparel design and apparel information system, in accordance with anexemplary embodiment. The application 2001 further described in FIGS.6A-6F (also referenced as “Shimmy Upskill”) provides a digital learninggame to users. Application 2001 communicates with a central computingplatform 2002 (also referenced as “Shimmy Platform” and/or the adaptiveapparel design computing device 110). The platform 2002, for example,provides artificial intelligence to identify 2-D shapes and common fixesto patterns and sewing based on fit problems, apparel vocabulary,operation instructions in multiple languages, training modules forspecific machines and CAD platforms, and certification andapprenticeship credentialing. Platform 2002 also includes a user'sinnate problem solving mental models and rates of change in machinepurchasing and planned purchasing based on geography (in addition toplatform 306). Platform 2003 includes an exemplary embodiment set forthin FIGS. 12-19 that includes job descriptions and job locationinformation. Platform 2004 includes an apparel automation customers:factory owners, machine companies, governments output to users: baselineskills assessment and training needs within a population and researchproducts.

The description herein is presented to enable any person skilled in theart to create and use a computer system configuration and related methodand systems for generating virtual items within a facility. Variousmodifications to the example embodiments will be readily apparent tothose skilled in the art, and the generic principles defined herein maybe applied to other embodiments and applications without departing fromthe spirit and scope of the invention. Moreover, in the followingdescription, numerous details are set forth for the purpose ofexplanation. However, one of ordinary skill in the art will realize thatthe invention may be practiced without the use of these specificdetails. In other instances, well-known structures and processes areshown in block diagram form in order not to obscure the description ofthe invention with unnecessary detail. Thus, the present disclosure isnot intended to be limited to the embodiments shown, but is to beaccorded the widest scope consistent with the principles and featuresdisclosed herein.

In describing embodiments, specific terminology is used for the sake ofclarity. For purposes of description, each specific term is intended toat least include all technical and functional equivalents that operatein a similar manner to accomplish a similar purpose. Additionally, insome instances where a particular exemplary embodiment includes amultiple system elements, device components or method steps, thoseelements, components or steps can be replaced with a single element,component or step. Likewise, a single element, component or step can bereplaced with multiple elements, components or steps that serve the samepurpose. Moreover, while embodiments have been shown and described withreferences to particular embodiments thereof, those of ordinary skill inthe art will understand that various substitutions and alterations inform and detail can be made therein without departing from the scope ofthe invention. Further still, other aspects, functions and advantagesare also within the scope of the invention.

Exemplary flowcharts are provided herein for illustrative purposes andare non-limiting examples of methods. One of ordinary skill in the artwill recognize that exemplary methods can include more or fewer stepsthan those illustrated in the exemplary flowcharts, and that the stepsin the exemplary flowcharts can be performed in a different order thanthe order shown in the illustrative flowcharts.

Although the present invention and its advantages have been described indetail, it should be understood that various changes, substitutions andalterations can be made herein without departing from the spirit andscope of the invention as defined in the appended claims.

The present invention will be further illustrated in the followingExamples which are given for illustration purposes only and are notintended to limit the invention in any way.

Having thus described in detail preferred embodiments of the presentinvention, it is to be understood that the invention defined by theabove paragraphs is not to be limited to particular details set forth inthe above description as many apparent variations thereof are possiblewithout departing from the spirit or scope of the present invention.

1. A system for training a user to label and code digital files formeasuring skills, three-dimensional garment design and three-dimensionalmodel utilization, machine basics, maintenance and finding employmentthe system comprising: a database storing at least one digital fileincluding a pattern having multiple pattern pieces; a user interfaceimplemented through a computing device, the user interface configured toprovide visual and auditory instructions in a local language of the userfor each module in a plurality of learning modules; and computerexecutable instructions that when executed by one or more processorsimplement the plurality of learning modules including a setup forcutting module that: measures human skills comprising a series ofquestionnaires and game-based trainings that test interest, aptitude,and willingness to pursue training; displays a visual representation ofeach of the multiple pattern pieces for identification of types ofpattern pieces and numbers of pieces to cut; displays identifiers ofdifferent types of pattern pieces, each identifier including a name ofthe type of pattern piece in the local language; displays identifiersfor numbers of pattern pieces to cut, each identifier including a nameof the number of pattern pieces in the local language; for each patternpiece, receives a selection of the visual representation of the patternpiece, receives a selection of a corresponding identifier for the typeof pattern piece, and provides a visual indication of whether theselection of the corresponding identifier for the type of pattern pieceis correct; for each pattern piece, receives a selection of a number ofpattern pieces to cut and provides a visual indication of whether theselection of the number of pattern pieces to cut is correct; providesactive learning games that capture decisions and collects a dataset fortraining future sewing equipment and robotics mental models; andprovides trainees collective member training/vetting/placement financialcoaching via partner application programming interfaces (APIs) andpublicly available datasets.
 2. The system of claim 1, furthercomprising computer executable instructions that when executed by theone or more processors implement a creation of markers for layout modulethat: provides a visual representation of each of the multiple patternpieces for layout for cutting with each visual representation includinga grain line for the pattern piece; provides a visual representation ofmaterial on which to lay out the pattern pieces; displays controls fordifferent types of transformation operations; receives a selection of atleast one of the multiple pattern pieces, a selection of a control for atransformation operation on the selected at least one pattern piece, anddisplays a visual representation of the transformation performed on theat least one pattern piece; and for each of the multiple pattern pieces,receives a selection of the pattern piece and a movement of the selectedpattern piece onto the visual representation of the material andrendering the movement and positioning of the selected pattern piece ona display of the user interface.
 3. The system of claim 2, furthercomprising computer executable instructions that when executed by theone or more processors implement a digital assembly module that:displays a visual representation of a front side of a three-dimensionalmodel, and a visual representation of a back side of a three-dimensionalmodel for fitting the pattern to the model; displays a visualrepresentation of each of the multiple pattern pieces for fitting on thethree dimensional model; receives a selection of at least one of themultiple pattern pieces, a selection of a control for a transformationoperation on the selected at least one pattern piece, and display avisual representation of the transformation performed on the at leastone pattern piece; and for each of the multiple pattern pieces, receivesa selection of the pattern piece and a movement of the selected patternpiece onto one of the visual representations of the three-dimensionalmodel and rendering the movement and positioning of the selected patternpiece on the display of the user interface.
 4. The system of claim 1,further comprising computer executable instructions that when executedby the one or more processors implement a pattern piece identificationmodule that: displays examples of different types of pattern pieces eachlabeled with the type of pattern piece in the local language; for eachexample pattern piece, prompts the user to speak the name of the type ofexample pattern piece in the local language, and records the spoken nameof the type of example pattern piece; and provides data representativeof the spoken name of the example pattern along and an identification ofthe type of example pattern piece to a natural language processingsystem to improve natural language processing of garment-relatedlanguage in the user's local language with the user's dialect.
 5. Thesystem of claim 4, wherein the pattern piece identification modulefurther: displays a visual representation of each of the multiplepattern pieces for identification of the pattern pieces; displaysidentifiers of different types of pattern pieces, each identifierincluding a name of the type of pattern piece in the local language; andfor each pattern piece, receives a selection of the visualrepresentation of the pattern piece, receives a selection of acorresponding identifier for the type of pattern piece, and provides avisual indication of whether the selection of the correspondingidentifier for the type of pattern piece is correct.
 6. The system ofclaim 2, wherein the display of controls for different types oftransformation operations includes display of schematic depictions ofthe transformation operations.
 7. The system of claim 1, wherein thedisplay of identifiers of different types of pattern pieces and thedisplay of the one or more identifiers for numbers of pattern pieces tocut is in response to receiving the selection of the visualrepresentation of the pattern piece.
 8. The system of claim 2, whereinthe display of controls for different types of transformation operationsis in response to the selection of at least one of the multiple patternpieces.
 9. The system of claim 2, wherein the transformation operationsinclude rotate, reflect, and copy.
 10. The system of claim 1, furthercomprising computer executable instructions that when executed by theone or more processors cause the user interface to: display a logininterface to the user; and receive information regarding a username anda password from the user.
 11. The system of claim 1, further comprisingcomputer executable instructions that when executed by the one or moreprocessors cause the system to access information regarding a mobileaddress of the computing device and store the accessed informationregarding the mobile address and information associating the mobileaddress with a user.
 12. The system of claim 1, further comprisingcomputer executable instructions that when executed by the one or moreprocessors cause the system to store information regarding the users'completion of each module associated with information identifying theuser.
 13. The system of claim 1, further comprising computer executableinstructions that, when executed by the one or more processors, causethe system to record information regarding correct and incorrectselections by the user, regarding correct and incorrect positioning ofpattern pieces on the visual representation of the material, regardingcorrect and incorrect movements of pattern pieces onto the visualrepresentation of the material, and/or regarding correct and inmovements of pattern pieces onto the visual representations of thethree-dimensional model.
 14. The system of claim 1, further comprisingcomputer executable instructions that, when executed by the one or moreprocessors, cause the system to transmit information to the user via thecomputing device after completion of one or more modules.
 15. The systemof claim 14, wherein the information transmitted is based, at least inpart, on one or more scores of the user's performance during one or moreof the learning modules.
 16. The system of claim 1, further comprisingcomputer executable instructions that, when executed by the one or moreprocessors, cause the user interface to display graphical indicators ofsuccessful completion of one or more modules within a training sessionand during one or more prior training sessions.
 17. The system of claim1, wherein the user interface is implemented and the plurality oflearning modules are implemented as a web-based application on thecomputing device that is hosted by a remote server.
 18. The system ofclaim 1, wherein the computing device comprises a touch screen and atleast some of the user selections are received via a touch screeninterface of the computing device.
 19. A method for training a user tolabel and code digital files for three-dimensional garment design, themethod comprising: providing visual and auditory instructions in a locallanguage of the user on a computing device; displaying a visualrepresentation of each of the multiple pattern pieces for identificationof types of pattern pieces and numbers of pieces to cut; displayingidentifiers of different types of pattern pieces, each identifierincluding a name of the type of pattern piece in the local language;displaying identifiers for numbers of pattern pieces to cut, eachidentifier including a name of the number of pattern pieces in the locallanguage; for each pattern piece, receiving a selection of the visualrepresentation of the pattern piece, receiving a selection of acorresponding identifier for the type of pattern piece, and providing avisual indication of whether the selection of the correspondingidentifier for the type of pattern piece is correct; and for eachpattern piece, receiving a selection of a number of pattern pieces tocut and providing a visual indication of whether the selection of thenumber of pattern pieces to cut is correct.
 20. The method of claim 19,further comprising: providing a visual representation of each of themultiple pattern pieces for layout for cutting with each visualrepresentation including a grain line for the pattern piece; providing avisual representation of material on which to lay out the patternpieces; displaying controls for different types of transformationoperations; receiving a selection of at least one of the multiplepattern pieces, a selection of a control for a transformation operationon the selected at least one pattern piece, and displaying a visualrepresentation of the transformation performed on the at least onepattern piece; and for each of the multiple pattern pieces, receiving aselection of the pattern piece and a movement of the selected patternpiece onto the visual representation of the material and rendering themovement on a display of the computing device.
 21. The method of claim19, further comprising: displaying a visual representation of a front ofa three-dimensional model and a visual representation of a back of athree-dimensional model for fitting the pattern to the model; displayinga visual representation of each of the multiple pattern pieces forfitting on the three-dimensional model; receiving a selection of atleast one of the multiple pattern pieces, a selection of a control for atransformation operation on the selected at least one pattern piece, anddisplaying a visual representation of the transformation performed onthe at least one pattern piece; and for each of the multiple patternpieces, receiving a selection of the pattern piece and a movement of theselected pattern piece onto the visual representation of the materialand rendering the movement on the display.
 22. The method of claim 19,further comprising: displaying examples of different types of patternpieces each labeled with the type of pattern piece in the locallanguage; for each example pattern piece, prompting the user to speakthe name of the type of example pattern piece in the local language, andrecording the spoken name of the type of example pattern piece; andproviding data representative of the spoken name of the example patternalong and an identification of the type of example pattern piece to anatural language processing system to improve natural languageprocessing of garment-related language in the user's local language withthe user's dialect.
 23. The method of claim 19, further comprising:displaying a visual representation of each of the multiple patternpieces for identification of the pattern pieces; displaying identifiersof different types of pattern pieces, each identifier including a nameof the type of pattern piece in the local language; and for each patternpiece, receiving a selection of the visual representation of the patternpiece, receive a selection of a corresponding identifier for the type ofpattern piece, and providing a visual indication of whether theselection of the corresponding identifier for the type of pattern pieceis correct.
 24. The method of claim 20, wherein displaying controls fordifferent types of transformation operations includes displayingschematic depictions of the transformation operations.
 25. The method ofclaim 19, wherein the displaying of identifiers of different types ofpattern pieces and the displaying of the one or more identifiers fornumbers of pattern pieces to cut is in response to receiving theselection of the visual representation of the pattern piece.
 26. Themethod of claim 19, wherein the displaying of controls for differenttypes of transformation operations is in response to the selection of atleast one of the multiple pattern pieces.
 27. The method of claim 20,wherein the transformation operations include rotate, reflect, and copy.28. The method of claim 19, further comprising: displaying a logininterface to the user; and receiving information regarding a usernameand a password from the user.
 29. The method of claim 19, furthercomprising accessing information regarding a mobile address of thecomputing device and storing the accessed information regarding themobile address and information associating the mobile address with auser.
 30. The method of claim 19, further comprising storing informationregarding the users' completion of each module associated withinformation identifying the user.
 31. The method of claim 30, furthercomprising recording information regarding correct and incorrectselections by the user, regarding correct and incorrect positioning ofpattern pieces on the visual representation of the material, regardingcorrect and incorrect movements of pattern pieces onto the visualrepresentation of the material, and/or regarding correct and inmovements of pattern pieces onto the visual representations of thethree-dimensional model.
 32. The method of claim 19, further comprisingtransmitting information to the user via the computing device aftercompletion of one or more modules.
 33. The method of claim 32, whereinthe information transmitted is based, at least in part, on one or morescores of the user's performance during one or more of the learningmodules.
 34. The method of claim 19, further comprising providinggraphical indicators of successful completion of one or more moduleswithin a training session and during one or more prior trainingsessions.
 35. The method of claim 19, wherein the method is implementedas a web-based application on the computing device that is hosted by aremote server.
 36. The method of claim 19, wherein at least some of theuser selections are received via a touch screen interface of thecomputing device.
 37. A system for collaborative refining of digitaland/or physical garment prototypes, the system comprising: a database ofa plurality of apparel computer aided design (CAD)-based models; and anapplication accessed via a computing device and communicatively coupledto the database, the application configured to: measure human skillscomprising a series of questionnaires and game-based trainings that testinterest, aptitude, and willingness to pursue training; receiveinformation identifying a first selected apparel CAD-based model of theplurality of apparel CAD-based models; display a graphicalrepresentation of the first selected apparel CAD-based model; modify aview of the graphical representation of the first selected apparelCAD-based model based on user input received via a user interface of thecomputing device; display annotation tools for annotation of the firstselected apparel CAD-based model and receive input for annotation from auser via the annotation tools or via speech processed via a naturallanguage processing tool; and display an indication of the annotation onthe display of the graphical representation of the identified apparelCAD-based model.
 38. The system of claim 37, wherein the application isfurther configured to: store the annotation input associated with thefirst selected CAD-based modal in the database and store a time that theinput for annotation was received or a time that the annotation inputwas stored; receive from a user, an identification of a file to beuploaded, associated with the first selected apparel CAD-based model;and store the identified file associated with the first selected apparelCAD-based model in the database.
 39. The system of claim 37, wherein theapplication is further configured to provide a notification to one ormore additional users regarding a change in or an addition to the storedinformation associated with the first selected apparel CAD-based modelin the database.
 40. The system of claim 37, wherein the system furthercomprises the application executing on a second computing device,wherein the application executed on the second computing device isfurther configured to: receive information identifying the firstselected apparel CAD-based model; and display a graphical representationof the first selected apparel CAD-based model including an indication ofthe annotation.
 41. The system of claim 40, where the second computingdevice has a default language preference different than a language ofthe annotation input, the application executing on the second computingdevice is further configured to display the annotation input in thedefault language of the second computing device.
 42. The system of claim40, wherein the application executing on the second computing device isfurther configured to: receive a second annotation input from a user ofthe second computing device; and store the second annotation inputassociated with the first selected CAD-based modal in the database. 43.The system of claim 37, wherein the information identifying a firstselected apparel CAD-based model of the plurality of apparel CAD-basedmodels obtained from image data acquired from an imaging device of thecomputing device.
 44. The system of claim 37, wherein the application isfurther configured to: display information regarding the identifiedfirst selected apparel CAD-based model; and request confirmation of theselection of the identified first selected apparel CAD-based model. 45.The system of claim 37, wherein the application is further configured toguide a user through a fit session for the identified first selectedapparel CAD-based model.
 46. The system of claim 45, wherein guiding theuser through the fit session for the identified first selected apparelCAD-based model comprises: displaying a request for one or more photosof a garment corresponding to the first selected apparel CAD-based modelon a fit model and enabling the user to select one or more photos forupload or displaying one or more previously uploaded photos of thegarment on a fit model.
 47. The system of claim 45, wherein guiding theuser through a fit session for the identified first selected apparelCAD-based model comprises, for each of a plurality of points of measure:providing a graphical description of the point of measure; receiving anaudio input from a user regarding the point of measure; and displaying anumerical value corresponding to the user's audio input for the point ofmeasure and graphical indicators for acceptance or rejection of thenumerical value.
 48. The system of claim 47, wherein guiding the userthrough a fit session for the identified first selected apparelCAD-based model further comprises, for each of the plurality of pointsof measure: displaying a graphical indication of whether the acceptednumerical value corresponding to the user's audio input for the point ofmeasure is within tolerance for the model.
 49. The system of claim 45,wherein guiding the user through a fit session for the identified firstselected apparel CAD-based model further comprises: displaying a promptfor the user to provide audio comments regarding the fit; and receivingaudio input from the user regarding the fit and displaying comment textcorresponding to the audio input, the audio input converted to text vianatural language processing relying on a garment-specific corpus oflanguage.
 50. The system of claim 45, wherein guiding the user through afit session for the identified first selected apparel CAD-based modelfurther comprises: displaying comments of other users regarding theapparel CAD-based model or the fit.
 51. The system of claim 37, whereinapplication is implemented as a web based application on the computingdevice that is hosted by a remote server.
 52. The system of claim 37,wherein the active learning sewing game tests sewing skills.
 53. Thesystem of claim 37, wherein the active learning sewing game utilizesgame interfaces to test hand-eye coordination, eyesight, and dexterityrelated to material handling.
 54. The system of claim 37, wherein theactive learning sewing game teaches stitch identification and teachestrainees what the most common machines in a factory look like.
 55. Thesystem of claim 37, wherein the active learning sewing game applicationuses game mechanics to teach what kind of thread is used for varioustypes of garments.
 56. The system of claim 55, wherein the stitches areused for Knits: 504, 406, 401 and which are for Wovens: 301, 516 (401 &504 combined).
 57. The system of claim 37, wherein users are able toidentify the stitches by sight at mastery of the learning module in theactive learning sewing game application.
 58. The system of claim 37,wherein the active learning sewing game application uses game mechanicsto teach stitch count and thread size selection for fabrics that impactssewing output.
 59. The system of claim 37, wherein the active learningsewing game application uses game mechanics to teach stitch qualitystandards and identify defects.
 60. The system of claim 59, wherein thestitch quality standards is to identify what is a good balanced stitchversus a bad imbalanced stitch.
 61. The system of claim 60, wherein theactive learning sewing game application uses game mechanics to teachusers what to do when a needle is damaged, causing stitch formation tobe off standard.
 62. The system of claim 61, wherein the sewn tradescollective member training/vetting/placement financial coaching connectsto employment sites and feeds in local job opportunities that matchtrainees' skill levels.
 63. The system of claim 62, wherein the sewngoods workforce practitioner/vetting/placement financial coaching helpstrainees understand wages, tax deductions, and the logistical realitiesof commuting to the job.
 64. The system of claim 63, wherein the sewngoods workforce practitioner/vetting/placement financial coaching allowshired workers to indicate their commitment to attend the shift, aidingin better workforce predictions and better throughput estimates to afactory's customers.
 65. The system of claim 64, wherein the sewn goodsworkforce practitioner/vetting/placement financial coaching enablesfactory hiring managers to predict how many workers will attend upcomingshifts.
 66. The system of claim 65, wherein the sewn goods workforcepractitioner/vetting/placement financial coaching enables factory hiringmanagers to vet candidates within the app and schedule interviews. 67.The method of claim 19, wherein the sewn goods workforcepractitioner/vetting/placement financial coaching enables factory hiringmanagers to vet candidates within the app and schedule interviews. 68.The method of claim 67, wherein the active learning sewing game testssewing skills.
 69. The method of claim 68, wherein the active learningsewing game utilizes game interfaces to test hand-eye coordination,eyesight, and dexterity related to material handling.
 70. The method ofclaim 69, wherein the active learning sewing game teaches stitchidentification and teaches trainees what the most common machines in afactory look like.
 71. The method of claim 70, wherein the activelearning sewing game application uses game mechanics to teach what kindof thread is used for various types of garments.
 72. The method of claim71, wherein the stitches are used for Knits: 504, 406, 401 and which arefor Wovens: 301, 516 (401 & 504 combined).
 73. The method of claim 72,wherein users are able to identify the stitches by sight at mastery ofthe learning module in the active learning sewing game application. 74.The method of claim 73, wherein the active learning sewing gameapplication uses game mechanics to teach stitch count and thread sizeselection for fabrics that impacts sewing output.
 75. The method ofclaim 74, wherein the active learning sewing game application uses gamemechanics to teach stitch quality standards and identify defects. 76.The method of claim 75, wherein the stitch quality standards is toidentify what is a good balanced stitch versus a bad imbalanced stitch.77. The method of claim 76, wherein the active learning sewing gameapplication uses game mechanics to teach users what to do when a needleis damaged, causing stitch formation to be off standard.
 78. The methodof claim 77, wherein the sewn trades collective membertraining/vetting/placement financial coaching connects to employmentsites and feeds in local job opportunities that match trainees' skilllevels.
 79. The method of claim 78, wherein the sewn trades collectivemember training/vetting/placement financial coaching helps traineesunderstand wages, tax deductions, and the logistical realities ofcommuting to the job.
 80. The method of claim 79, wherein the sewntrades collective member training/vetting/placement financial coachingallows hired workers to indicate their commitment to attend the shift,aiding in better workforce predictions and better throughput estimatesto a factory's customers.
 81. The method of claim 80, wherein the sewngoods workforce practitioner/vetting/placement financial coachingenables factory hiring managers to predict how many workers will attendupcoming shifts.
 82. The method of claim 81, wherein the sewn goodsworkforce practitioner/vetting/placement financial coaching enablesfactory hiring managers to vet candidates within the app and scheduleinterviews.